A new index for the analysis of heart rate variability dynamics: characterization and application

A new index for the analysis of the heart rate variability (HRV) dynamics is presented. The proposed index (acceleration change index (ACI)) characterizes the sign of the differences of a time series. A theoretical study shows an expression that relates ACI and the autocorrelation function of the time series. This formula is tested and validated with different simulated time series (uncorrelated noise, sinusoidal and fractional Brownian motion). Next, ACI is applied to RR time series from healthy subjects showing that ACI decreases with periodic controlled breathing, increases during exercise, and it has a lower value at night than during the day. In a preliminary study, ACI has been shown to be lower in healthy subjects than in patients who had suffered a myocardial infarction one month previously. ACI can be employed as a fast and robust new marker of the HRV dynamics.     

Comparison of Polar® RS800G3™ heart rate monitor with Polar® S810i™ and electrocardiogram to obtain the series of RR intervals and analysis of heart rate variability at rest

The Polar^® RS800G3^? rate monitor was released in the market to replace the Polar^® S810i^?, and few studies have assessed that the RR series obtained by this equipment is reliable for analysis of heart rate variability (HRV). We compared HRV indexes among the devices Polar^® RS800G3^?, Polar^® S810i^? and eletrocardiogram (ECG) to know whether the series of Polar^® RS800G3^? are as reliable as those devices already validated. We analysed data from 30 healthy young adults, male, with an average age of 20·66 ± 1·40 years, which had captured the heart rate beat to beat in the three devices simultaneously with spontaneously breathing, first in the supine position and subsequently sit both for 30 min. The obtained series of RR intervals was used to calculate the indexes of HRV in the time domain (SDNN and RMSSD) and in the frequency domain (LF, HF and LF/HF). There were no significant differences in HRV indexes calculated from series obtained by the three devices, regardless of the position analysed, and a high correlation coefficient was observed. The results suggest that the Polar^® RS800G3^? is able to capture series of RR intervals for analysis of HRV indexes as reliable as those obtained by ECG and Polar^® S810i^?.     

Heart rate variability analysis in the assessment of autonomic function in heart failure

Heart rate is not static, but rather changes continuously in response to physical and mental demands. In fact, an invariant heart rate is associated with disease processes such as heart failure. Heart rate variability analysis is a noninvasive technique used to quantify fluctuations in heart rate. In this article, the authors review neural control of heart rate, briefly describe heart rate variability, and summarize research data demonstrating that heart failure is associated with altered heart rate variability. In addition, the authors present evidence that heart failure patients with decreased heart rate variability are at risk for future cardiac events, heart transplantations, and death.     

Application of threshold-based acceleration change index (TACI) in heart rate variability analysis

Heart rate variability (HRV) analysis is a non-invasive and reliable means to assess an autonomic nervous system (ANS) function. Heart rate is a non-stationary signal that may contain indicators of current diseases and sometimes warnings about impending diseases. In this paper, we have proposed the threshold-based acceleration change index (TACI) for HRV analysis, which is calculated from the sign of differences of RR time series characterizing the dynamics of threshold crossings. It was found that TACI is robust in classifying various groups under different physiological and pathological conditions. We have studied the behavior of TACI for simulated time series (uncorrelated random data, sinusoidal time series and logistics map time series) and its robustness in the presence of artifacts for RR time series. The performance of TACI is evaluated for classifying normal sinus rhythm (NSR), congestive heart failure (CHF) and atrial fibrillation (AF). An unpaired Student's t-test was used to check significant differences between these groups and the degree of separation between these groups was quantified by using the area of a receiver operator curve.     

Fetal heart rate variability analysis for neonatal acidosis prediction

Journal of Clinical Monitoring and Computing - Fetal well-being during labor is usually assessed by visual analysis of a fetal heart rate (FHR) tracing. Our primary objective was to evaluate the...     

Effects of athletic training on heart rate variability triangular index

The purpose of this study was to assess the heart rate variability triangular index (HRVI) in elite track and field athletes. Sixty healthy males (mean aged 22.1 +/- 3.5 years) -15 long distance runners (group A), 15 speed runners (Group B), 15 throwers (Group C) and 15 non-trained subjects (Group D) were submitted to spiroergometric test, m-mode echocardiography and 24-h ambulatory ECG monitoring. The HRVI, mean heart rate, mean interval between two consecutive R waves of the QRS complexes (R-R interval) and standard deviation of the R-R (SDRR) were assessed through time domain method on computed 24-h Holter recordings. The HRVI and the SDRR were 62.2 +/- 9.6 and 220 +/- 40 ms correspondingly in group A, 52.7 +/- 6.0 and 210 +/- 40 ms in B, 44.5 +/- 5.3 and 180 +/- 40 ms in C, 39.3 +/- 6.4 and 180 +/- 30 ms in D. The HRVI and the mean R-R were found to differ statistically between groups A, B and C versus D (P < 0.05). However, the higher value in HRVI was found in group A. Maximal oxygen consumption (VO2max) was 62.0 +/- 4.4 ml kg-1 min-1 in group A, 52.7 +/- 6.0 in group B, 44.6 +/- 5.3 in C and 41.6 +/- 6.0 in D. The higher value in VO2max was also found in group A. The left ventricular mass index (LVMI) and end-diastolic volume index (EDVI) were 136 g m-2 and 83 ml m-2 correspondingly in group A, 136 and 79 in B, 124 and 56 in C and 88 and 55 in group D. The HRVI was found to have a significant relationship with VO2max and EDVI only in group A. On the other hand, no significant relationships were found between HRVI and LVMI in all groups. It is concluded, that the enhanced HRVI in athletes is affected by exercise training pattern. Moreover, HRVI depends on the level of VO2max in endurance-trained, but is independent from the extent of myocardial hypertrophy in all types of training.     

The corner frequencies of the ECG amplifier for heart rate variability analysis

Heart rate variability (HRV) analysis is considered a popular method both in clinical and research fields. However, several ignored technical artifacts may falsify its measurements. The current study investigates the effects of corner frequencies of the ECG amplifier on the precision of RR-interval detection. Clear or noise-corrupted ECG records with predefined parameters consisting of 21 cycles were generated, played back through analog filters and data-logged on a Pentium-based computer with a DaqBoard2000 data acquisition card. 0.1-10 Hz second-order high pass and 20-100 Hz fourth-order low pass Bessel and Butterworth filters were used. The RR-intervals were measured between seven reference points of the ventricular complexes before and after filtering. High and low pass at every frequency cutoff and with both filter types results in correct RR-intervals within 1 ms error. However, a lower cutoff below 1 Hz is needed to maintain ECG morphology. AC interference or Gaussian random noise can falsify the measured RR-intervals up to 16 or 34 ms, respectively. These errors may be reduced to 1-4 ms with appropriate low pass filters. A frequency range of 0.5-20 Hz for the ECG amplifier can be sufficient for HRV analysis reducing the errors from AC interference or random noise.     

Time-frequency analysis of heart rate variability using short-time fourier analysis

This study was done to introduce new parameters derived by time frequency analysis of heart rate variability data. Four simulation experiments were carried out to compare the short-time Fourier transform (STFT) analysis method to the traditional overall spectral analysis method. Sinusoidal signals were generated with identical total power in the high-frequency band, but varying time-frequency and time-amplitude information. The STFT method was also applied to heart rate variability data from the stages of normal human sleep. Data analysis included computation of the power in the high-frequency band by overall spectral analysis. The instability coefficients (ICs) of the frequency and power in the high-frequency band were derived by STFT analysis. The ICs derived by the STFT method were able to describe time-frequency and time-amplitude variations in sinusoidal signals which contained identical total power in a specified frequency range. The ICs of the frequency and power were able to differentiate variations in vagal activity between the stages of human sleep and waking. The ICs represent new parameters derived by the STFT method, and allow the detection and quantification of short-lasting time-frequency and time-amplitude variations that remain obscured by overall spectral analysis.     

Power spectrum analysis of heart rate variability for cerebral palsy patients

OBJECTIVE: The prevalence of bowel and bladder dysfunction, hyperhidrosis, and poor cardiopulmonary endurance is higher for children with cerebral palsy than for the general population. The purpose of this study was to investigate the autonomic function for patients with cerebral palsy. DESIGN: Thirty patients with cerebral palsy and 30 control subjects were enrolled in this study. Power spectrum analysis of heart rate variability was performed under standardized conditions. RESULTS: In both the supine and head-up positions for test subjects, there was no significant difference for the low frequency component of heart rate variability, high frequency component of heart rate variability, or the low frequency/high frequency ratio between the study and control groups. A significantly greater low frequency component of heart rate variability, smaller high frequency component of heart rate variability, and greater low frequency/high frequency ratio while in the head-up position compared with the supine position was noted for the control group, which implies normal sympathovagal balance. A similar phenomenon was not observed for the study group. CONCLUSIONS: The disturbed balance of activity between the sympathetic and parasympathetic nervous system observed in the study might result from the loss of hemispheric influence in patients with cerebral palsy; however, further investigation is clearly necessary.     

On- and off-responses of heart rate to exercise - relations to heart rate variability

During physical exercise, heart rate (HR) increases by parasympathetic withdrawal and increase of sympathetic activity to the heart. HR variability (HRV) in time and frequency domains provides information about autonomic control of the cardiovascular system. Non-linear analysis using the Poincaré plot method is able to reveal supplementary information about cardiac autonomic control. The aim of this study was to determine the association between HRV parameters, the initial increase of HR at the onset of exercise (on-response) and HR decrease in the recovery phase after acute exercise (off-response). HR was continuously monitored in 17 healthy male subjects (mean age: 20.3 +/- 0.2 (SEM) years) at rest (25 min supine; 5 min standing), during exercise (8 min of step test at 70% of maximal power output) and in the recovery phase (30 min supine). HRV analysis in time and frequency domains and evaluation of the Poincaré plot measures (length, widths) were performed on selected segments of HR time series. HR on- and off-responses were quantified using an exponential curve fitting technique. The time constants T(on) and T(off), representing the rate of on- and off-responses to exercise, were computed. Postexercise HRV indices and time constant of on-response - T(on) - to exercise were negatively correlated. From preexercise HRV indices, only Poincaré plot parameters were correlated with T(on). No correlation between HRV indices and parameters of off-response was found. In conclusion, preexercise HRV parameters are not closely correlated with the rate of cardioacceleration at the onset of exercise and cannot predict the rate of HR recovery. On the other hand, postexercise HRV parameters are related to the rate of initial adjustment of HR to exercise referring to the importance of rapid HR on-response for a faster recovery after exercise.     

Pulse rate variability is not a surrogate for heart rate variability.

To investigate the differences between heart rate (HR) variability and pulse rate (PR) variability, short-term variability of finger pulse wave and ECG signals were studied in 10 children with a fixed ventricular pacemaker rhythm (80 beats/min). Ten healthy children in sinus rhythm served as a reference population. Distal PR and HR were measured continuously using a Finapres device and an ECG respectively. Power spectra for HR and PR were calculated in both the supine and orthostatic positions. In paced subjects, PR spectra exhibited the characteristic respiratory peak, although the HR spectra were flat. Similarly, in healthy children the respiratory fluctuations were more pronounced when calculated from the finger pulse wave signal compared with the ECG signal. The overestimation of HR respiratory fluctuation resulting from distal PR measurement was more pronounced in the standing position; however, this postural effect was demonstrated only in healthy subjects. We observed mechanical respiratory modulation of distal PR independent of classical HR modulations. Our results suggest a mechanical respiratory influence via cardiac output and aortic transmural pressure changes on pulse wave velocity. We conclude that respiratory PR variability does not precisely reflect respiratory HR variability in standing healthy subjects and in patients with low HR variability. Consequently, HR modulation should be studied using the ECG signal rather than the distal pulse wave signal. However, when ECG recording is not available, the distal pulse wave is an acceptable alternative.     

Cosinor analysis of heart rate variability in ambulatory migraineurs

OBJECTIVE: To clarify whether the circadian rhythm of heart rate variability parameters can be identified in patients with migraine during a headache-free period and to identify any specific pattern of the circadian rhythm of heart rate variability, using time-domain and spectral analysis and cosinor rhythm analysis of heart rate variability during normal daily activity. METHODS: Forty-eight-hour Holter electrocardiograms were recorded for 27 patients with migraine during headache-free periods and 24 healthy controls during free activity. The circadian rhythms of heart rate fluctuation parameters, that is, mean interval, standard deviation, root-mean-square successive differences (RMSSD), %RR50, and low (0. 020 to 0.150 Hz) and high frequency (0.150 to 0.400 Hz) heart rate fluctuations were analyzed with the group mean cosinor method. RESULTS: The group mean cosinor analysis and the acrophase-amplitude analysis demonstrated significant differences in circadian rhythm in SD, RMSSD, %RR50, and high frequency between the group with migraine and controls. The amplitudes of SD, RMSSD, %RR50, and high frequency in the group with migraine were smaller than those in controls, which implied parasympathetic hypofunction in migraineurs. There were no significant differences in the MESOR (midline estimating statistic of rhythms) of the analyzed heart rate parameters except for low frequency. The MESOR of low frequency in the migraineurs was significantly smaller than that in the controls. CONCLUSIONS: Patients with migraine have hypofunction in the parasympathetic nervous system during normal daily activity in the headache-free period.     

早期糖尿病肾病心率变异性的临床分析

目的探讨早期糖尿病肾病患者心率变异的特点。方法对30例早期2型糖尿病肾病患者和30例无并发症2型糖尿病对照者,进行24h动态心电图监测,对心率变异性参数进行分析比较。结果早期2型糖尿病肾病组的心率变异性参数均显著低于无并发症2型糖尿病对照组(P<0.05)。结论早期糖尿病肾病较无并发症糖尿病患者的自主神经功能损伤更加严重。     

Spectral components of heart rate variability determined by wavelet analysis

Spectral components of heart rate variability (HRV) are determined in the time-frequency domain using a wavelet transform. Based on the finer estimation of low-frequency content enabled by the logarithmic resolution of the wavelet transform, corrections of spectral intervals, already defined by Fourier and model based methods, are proposed. The characteristic peaks between 0.0095 and 0.6 Hz are traced in time and four spectral intervals are defined, I (0.0095-0.021 Hz), II (0.021-0.052 Hz), III (0.052-0.145 Hz) and IV (0.145-0.6 Hz), within which peaks are located for all subjects included. These intervals are shown to be invariant regardless of the age and the state of the system. We also show that the frequency and power of the spectral components are related to age, AMI and particularly to type II diabetes mellitus.     

Heart rate variability analysis: a tool to assess cardiac autonomic function

Heart rate monitoring is commonly used to provide an acute indicator of an individual's cardiovascular status and responsiveness. An increasingly popular technique involves quantifying the very small amounts by which the heart rate changes from one cardiac cycle to the next. This "heart rate variability (HRV) analysis" provides a substantial amount of additional information about the cardiovascular system and enables quantification of cardiac regulatory influences on the autonomic nervous system. The autonomic nervous system consists of two main components: the sympathetic system and the parasympathetic system. The relative influence of these two components on the sino-atrial node of the heart determines the heart rate. A number of physiological factors, including blood pressure and respiratory rate, can have a profound effect on this autonomic "balance." HRV analysis therefore provides a noninvasive method for investigating the dynamic influence of changing physiological parameters on cardiac regulation.